Open Source MCP CLient Library

@bittush8789

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Basic information

About Open Source MCP CLient Library

No overview available yet

#mcp #mcp-server #open-source #llm #agent

Open Source MCP CLient Library config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Open Source MCP CLient Library tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Open Source MCP CLient Library?

Open Source MCP CLient Library (mcp-use) is an open source Python library that connects any LangChain-supported LLM to MCP tools, enabling developers to build custom agents with tool access without using closed source or application clients.

How to use Open Source MCP CLient Library?

Install via pip install mcp-use and optionally a LangChain provider package (e.g., langchain-openai). Configure an MCP server using a dictionary or JSON file, create an MCPClient and a LangChain LLM that supports tool calling, then create an MCPAgent and invoke await agent.run() with a query.

Key features of Open Source MCP CLient Library

Ease of use: create a first MCP agent with only 6 lines of code
LLM flexibility: works with any LangChain LLM supporting tool calling (OpenAI, Anthropic, Groq, etc.)
HTTP support: direct connection to MCP servers running on HTTP ports
Multi-server support: use multiple MCP servers simultaneously in a single agent
Tool restrictions: restrict potentially dangerous tools like file system or network access

Use cases of Open Source MCP CLient Library

Web browsing with Playwright to search and scrape the web
Searching Airbnb for accommodations using an MCP server
Creating 3D models in Blender via the Blender MCP server
Combining tools from multiple MCP servers (e.g., browsing + file operations)
Connecting to web-based MCP servers over HTTP for remote tool access

Frequently asked questions

What LLMs are supported?

Any LangChain-supported LLM that has tool calling capabilities, such as OpenAI, Anthropic, Groq, and Llama models.

How do I install the library?

Run `pip install mcp-use` and install the appropriate LangChain provider package (e.g., `langchain-openai`) for your chosen LLM.

How do I connect to MCP servers?

You can connect via stdio by specifying a command and arguments in the config, or via HTTP by providing a URL (e.g., `http://localhost:8931/sse`).

Can I restrict which tools the agent can use?

Yes, pass `disallowed_tools` to `MCPAgent` to block categories like `file_system` or `network`.

Can I use multiple MCP servers at the same time?

Yes, define multiple servers under `mcpServers` in your configuration and pass it to `MCPClient.from_dict()` or `from_config_file()`.

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